99 machine-learning "https:" "https:" "https:" "https:" "https:" "https:" uni jobs at Nature Careers
Sort by
Refine Your Search
-
Listed
-
Country
-
Field
-
research. These new faculty positions represents part of a major research initiative by VT located at both our main medical center campus in Roanoke (https://hst.vt.edu/campus.html ) as well as our facility
-
questions relevant to the advancement of human health. Appointees are expected to teach at the undergraduate or graduate level. The University of Chicago is a vibrant center of scientific discovery and
-
cohorts and data generation resources through highly collaborative clinical faculty. Ideal candidates will have expertise in computational modeling, machine learning, or algorithm development, with
-
assemble in infected cells and selectively package their RNA genomes. More information about the lab and their work can be found by visiting https://www.hhmi.umbc.edu . About the Postdoctoral Scientist role
-
of results. Highly motivated and have good communication, project management and organisational skills. Willing to learn new skills and techniques. Desirable Experience in proteomics and cancer models would be
-
training and research focus in statistics, data science, machine learning or artificial intelligence (as evidenced by thesis/dissertation topic and their publication record), and hold a PhD (or equivalent
-
Interfolio to: https://apply.interfolio.com/176454 The review of credentials will begin immediately and will continue until the position is filled. Equal Employment Opportunity Statement For people in the EU
-
periods for learning, and how individuals’ innate variations interact with experience to give rise to differences in learned behaviors. The team focuses on vocal learning in songbirds as a model system to
-
modelling, stem cell biology (animal-/humanderived tissues), micro-physiological systems (MPS), organ-on-chip, zoonotic diseases, drug/vaccine testing and validation for zoonotic diseases, machine learning in
-
, Cambridge, Heidelberg, Innsbruck, and Munich. The Stegle group is jointly based at DKFZ and EMBL and embedded in Heidelberg’s vibrant ecosystem for data science, machine learning, and computational biology